System Product Engineer (New or Recent Graduate)

Job Description

Why This Role: Build foundational infrastructure — simulation, automation, and AI-assisted workflows. Small team, high impact, and the opportunity to shape how system test development is done.

Build AI-native validation and test infrastructure enabling early system learning and workload-driven validation across the product lifecycle, reducing dependency on late-stage integration environments.

You will operate across compute, memory, and storage subsystems, enabling correlation between real workloads and system behavior.

Essential Duties And Responsibilities

• AI Workload Modeling & Generation
• Develop and analyze AI workloads, focusing on memory access characterization, and data movement behavior
• Generate trace-based and synthetic stress patterns for system-level validation
• Simulation-First Validation
• Build lightweight simulation and emulation environments (e.g., QEMU-based system models and customized modeling)
• Map workload to test prior to hardware availability
• Reduce dependency on full-system emulation/real hardware through independent, scalable frameworks
• AI-Assisted Test Infrastructure
• Build C/C++/Python-based automation frameworks with parallel execution, structured logging, and scalable data pipelines
• Convert product specifications into structured formats for AI-assisted code generation and automated validation
• Integrate AI tools for test content generation, debug acceleration, and log analysis
• Firmware & Test Content Development
• Develop workload-aware test firmware aligned with system-level use cases
• Enable functional coverage based on real workloads, not synthetic-only scenarios
• Data & AI-Driven Insights
• Build pipelines for data collection, failure classification, and pattern detection
• Apply ML techniques where appropriate for anomaly detection and failure clustering
• System Correlation
• Map workload behavior to system stress and device-level impact, enabling translation between real workloads and production test coverage
• Correlate across compute, memory, and storage subsystems

Qualifications

• Education: BS/MS/PhD in Electrical Engineering, Computer Engineering, or Computer Science
• Experience: 0–5+ years in validation, modeling, infrastructure development, or related fields
• Technical Skills: Strong Python skills; C/C++ a plus
• Experience or research background: Understanding of data movement and performance behavior across system components
• Key Traits: Builder mindset — tools, frameworks, infrastructure; Strong system and data intuition; Hands-on coder or effective AI workflow orchestrator — non-negotiable
• Additional Information: Builder mindset — tools, frameworks, infrastructure; Strong system and data intuition; Hands-on coder or effective AI workflow orchestrator — non-negotiable